Hotel Tech Insider

SPEAKER_02:
Because technology is great, everybody's collecting and saying the data, but what am I doing with the data? That is important. Big data is great. I'm an IT guy, so like you can imagine, I love data.

SPEAKER_03:
But the important part is not big data, it's smart data and what you're doing out of it.

SPEAKER_00:
From Hotel Tech Report, it's Hotel Tech Insider, a show about the future of hotels and the technology that powers them.

SPEAKER_01:
Today we chat with Martin Kemmer, the Managing Director of PlaceValue Hotels, a German brand of economy hotels with a big focus on technology. Martin started his career in IT and brings tons of technical expertise and passion to the hotel sector. In our conversation, we learn all about PlaceValue's tech stack and how Martin uses data to drive his decisions. Martin and his team have studied each facet of their booking and guest experience, and some of his learnings might surprise you. I like to start the conversations getting more of an understanding of your background and especially for our listeners so they can understand your career so far, the different roles you've worked in, and then how you got to your current role. So if you could walk me through your career, how you got to where you are today, and then what you're doing at the moment.

SPEAKER_02:
Yes. Well, I'm not a hotel first in my life. I studied economics at Humboldt University in Berlin, and I founded my first company in 2003 in the IT sector.

SPEAKER_03:
And the first years I built up IT companies.

SPEAKER_02:
And then around 2009, my best friend and best man, who is a hotelier, who's not unfortunately not with us anymore, he said, I need a silent investor in hotels. And that's when I got to know this little thing called hotels and I was always amazed about structures and everything and then I looked into it and I'm not good as a silent investor, I have to admit. So I went into hotels and I saw, wow, we're going back a hundred years technology wise. And yeah, well, I decided to change this and then we started with one and then now we have, we're just starting a new brand this month with seven hotels, which is AI first, and we're working on data ever since. And there were a couple of changes, and I'm a person who likes to build MVPs, minimal viable products. And I know in IT, minimal viable products are cheap and easy, but building a hotel property as an MVP, and I did a couple of those, is not that common. And we built now our final, there's never a final product, but there's That at the moment, the best product we have is in Karlsruhe, and this is a hotel that actually has a digital twin. So it is completely in building information modeling. Maybe I'm already going too deep into something in the introduction phase, but that is very interesting, how many data you're getting. And for example, in another property of us, which we developed 2017, which started 2017, we developed, it always takes about three years to develop a hotel. we figured out that with smart cameras, by making lines, we had yellow lines for guests, purple lines for employees, and lines that are not precise. But then when you put the purple lines for the employees together, you see that 12 meters of space is an equivalent of four full-time workers a year in just walking. So this is something where you have a data-driven mindset to make life a lot better. And a lot of my colleagues say they are looking at a bar and say the bar has to go there, or they're looking at a front desk, it looks best there. We are data-driven. So that's maybe the main difference. I like to learn a lot about customers. I like to learn about what is actually being used and not what are people telling that they're using. So that makes sense for you. So there are a lot of people that say we want to pool for example in a hotel but they never use it or they say the bar needs to be there or the front desk needs to be there maybe we should also look at the economics of it and maybe even save some steps because if you save 12 meters like i said you have saved four days and the return on investment is immediately there without any discomfort for anyone.

SPEAKER_01:
Well, let's dive right in because I would love to learn more about all of these things. So tell me a bit more about the smart cameras.

SPEAKER_02:
all this ages ago. That's the first part. That was only, you know, you only had the movement of the people and saying, OK, the person is moving from that side to that side. It's the same technology we're using or you are used to with cars. It's basically the same. We have next to this object a parking space with 600 lots. And so we use the same technology that we use to track cars, you know, where you have the license numbers and to open the or the parking spaces and everything. And then you need to know which car's inside, which car's outside. So basically it's the same camera system that is used for traffic control the whole time, just adapted to people. later on and i mean one of the great example of it they are doing this since i think twenty years to track the motions of people and how they flow and there's a lot of metadata there you can learn from this is not the personalized data just to understand that we don't look at these. images where you have the faces and everything. No, no. It's just the metadata of how people are running. And we only divide between employees or staff and a guest. And everybody who's not staff is guest.

SPEAKER_01:
And what sort of decisions do you use this data to make besides maybe the location of the bar?

SPEAKER_02:
The location of the bar is one of these easy things. And if I tell that colleagues of mine, they think, oh, yes, sure. But we never thought about this. But of course, in the hotel, we have peaks. And this data, the building data, is very important to make a satisfying customer journey. So for example, The data is also used to see the elevators. Usually in hotels, elevators open one side and they're all talking about the speed, how elevators go up and down. That is not that important. The important part is how fast are doors opening and closing. So just going from both sides, it's a huge difference. These are hundreds of small, really small incremental changes you're making out of this data. that at the end makes a lot of time saving for our customers. And to emphasize this, and we should go to the customers, it is for us, we figured out that time is very important for our guests because we are a standardized economy hotel concept, system hotel, economy hotel concept. That means that our guests are not coming for the hotel, Like, a lot of people think, yeah, we are going here, this system economy hotel, because we have a reason to be there.

SPEAKER_03:
Either you have business, you have a fare, you're meeting relatives. So we are not the center of the gravity of the guests, but we are, like I always say, Hotel is best if they are not noticeable what do i mean nobody says. What was punch again or if it says four hundred thousand times you want to work you only complain about the bond when it doesn't work when it says ok. It was late again, it was late again, but that you never look at the 200 times you went traveling with the Uber on the days before without any problems. I'm very happy about this.

SPEAKER_02:
The hotel, the best we can achieve is that we're not recognizable.

SPEAKER_03:
And I think that is a completely different mindset to a lot of other hotels because we are working. We have one persona that is, for example, a business woman that is in a telephone conference.

SPEAKER_02:
while she's checking in because she has no time.

SPEAKER_03:
So she doesn't want to have all this disturbing calls and everything. And she wants to go in the room, be in the room, find a desk where it's clean, where she can just continue working. And the hotel does not interfere with her work. And she's just, it's everything there. And it's, we say, just simplistic working. So to understand a little bit about this, what we learn about this smart technology, because technology is great.

SPEAKER_02:
Everybody's collecting and saying the data, but what am I doing with the data? That is important. Big data is great. I'm an IT guy.

SPEAKER_03:
So like you can imagine, I love data, but the important part is not big data, it's smart data and what you're doing out of it.

SPEAKER_01:
So I'm curious to learn how you are setting up your tech stack now to account for this sort of booking behavior in the future. So maybe starting with your PMS or your reservation system, how do you set it up for success when things get a little more advanced in the future?

SPEAKER_02:
So I'm not starting with a data lake and the total foundation of an IT stack now, because I think we're going there really a little bit into detail because we need a huge data lake with a golden record or even with a platinum record. So where the data is completely correct and everything is docked into this, maybe we go later on into that. So I'm just going into that. All the systems we're using are specialized systems. So a PMS should be a PMS, a property management system. It is not a revenue management system. It is not a customer relationship management system. These are all highly specialized systems that need to talking about it. And then again, now we're already getting this data lake for the experts who are listening. Because once you have all these systems, you need to transfer data from A to B. And sometimes it's best to have a huge data lake. to have all the information there and dock all the systems onto that one, because with a generalized data leak, it is much easier to connect the APIs to the different softwares, and you have to have all the data in the different softwares correct. So this is very, very important. So to start, we are very, very proud to work with Muse together. We actually were the ones who said, I talked to Richard, and said, we need a multi-property. Your program is great, but we need a multi-property. So together, and that's a great experience with Nios, was we built together a multi-property. They built it. We were the guinea pigs, to say, or the beta tester and said, this is what we need. And it was great because completely professional teams, their IT guys was our IT, we're working hand-in-hand to make it possible to have a multi-property system, which is customer-centric, which is going the new ways, where the data is already correct and where the data is live and all the other systems. So that is, for example, a huge success story to see how it works and how to get the data to get it easier and we try to get the news to make it as simple as possible for employees because you worked with Expedia you said and you know the old opera system where you have all this information and there is a great example where at least used to be that way, where you need the right information on top of it. So Google is the best example. At the beginning of Google, you only had this one search bar, nothing else. It was just the search bar. So why not, especially with hotel employees, make it as simple as possible and reduce the data they're seeing so they can actually work with the program. itself even easier. And that was one of the challenges we had with MUSE, not with MUSE, it was a challenge with the other PMSs that were actually solved with MUSE quite quick and quite good, that would make it easier. This donut principle, they have a great idea to make it a fantastic product to see, to have the people guided through that. And that makes it easier for the hotel employee or hotel staff And then the guest experiences, again, better once the staff is not going, I need to go into that menu to go that menu and to change that address. That is a little bit too. So the main data, that data that is highly used. So again, something where data driven is a huge advantage because most of the fields you're using maybe once a week or twice a week. So get these fields in the back and get the right menus in front. That is very, very important. It's that what I'm using always and in that context. And if you're going on, for example, then from Muse to the booking engine, to then the booking engine, where you have the preferences of the guests. I was talking about the preferences for the AI earlier. But now you see another use case for the preferences, higher floor, lower floor, right, left, because already in the booking engine, we can now, with Galvendi, get into that one and give the customer the right preferences. And now we are going into behavioral pricing with Galvendi, which is very, very important because it is already Common sense i would say behavior pricing so if you have just one room we figured out a lot of tests and say okay one room on the right side is sixty nine euros without breakfast and nine nine euros with breakfast. People choose to 80% 69 euros. Now you're making the same example and says, okay, 69 euros without breakfast, 99 euros with breakfast and 99 euros with breakfast and Riverview. It is two thirds of choosing now Riverview and breakfast instead of just the cheapest option and are more satisfied and happier and it's a win-win situation for everybody. So that is something we can do, for example, with partners like Galwendy and to just make this possible. And then, of course, the revenue management system. You asked about the technology stack. Our specialty is to put all the technology stacks together and find the right things. to match them and not develop everything ourselves can i or a i activities we develop a lot of ourselves because that's one of our core businesses but that part for example with advanced pricing revenue management systems and everything their partner like to add to this really great partner to find the right strategy for the right time at the right moment and not only do prices just for the room, but for every category, for every, if you're one person in a room or two persons, or even a family or other attributes, and then pricing for these attributes is very, very important. And to find the right pricing for these things, you also need a huge engine to calculate this and give always the right price and to find these right prices.

SPEAKER_01:
I want to take a step back and learn a little more about your booking engine, Galvendi. So you mentioned you have the option to test a few different options, like the room with breakfast versus Riverview and breakfast. Does the booking engine allow for A-B testing like that, or is that something that you need to kind of set up on your own?

SPEAKER_02:
Usually not using the word A-B testing because it makes a lot of people uncomfortable, but that's a lot we're doing. We're doing a lot of A and B testing. We also do a number that Galvani did and we worked with them together. eye-tracking and things like that to see where it is. And behavioral economics is Swirsky and thinking fast, thinking slow. It's the mother of this theory of behavioral economics and of course, nudging or animal spirit two other big influences here. So this is all very economical driven, so behavioral science driven. And I just mentioned three books I could mention more, The Invisible Game by Marcus Müller or others. And these scientific proven methods, if you test them, hotel yeast and my colleagues are usually, wow, that works and how good that works. It's something, yeah, people still believe in the hotel, or some people believe that the guest who's on the receptionist, the main guest, and we know our guests, but we don't know the huge masses of people we're serving every day. That is too much. So this is also, and it was Galbendi, it was possible exactly to do this. So we have at the beginning, too many choices and we had to reduce choices because choice architecture is very important. And it's A-B testing, but it's also trial and error, I have to admit. There is not everything we're trying is working. So again, here MVPs have a huge role into it, minimal viable products, because these minimal viable products is, yeah, we're testing this. And sometimes we figure, okay, this works in one location that is more business and trade show, other business and business, that doesn't work that good. So we need to adapt there and to have the algorithm learn from it, to build these huge data sets and to find similarities. I mean, of course, we're not there where Amazon was 10 years ago, and I wish the whole We would have started a lot earlier. The whole industry would have started earlier, but let's face it. We are there where we are there now and we catch up very fast because we can just learn from Amazon and co to customers who bought this product also bought this product. This works for the hotel industry too, because we get preferences quite quick from the customer and see them due to their actions, how they're I'm moving around and on websites and especially in the product and the great thing about hotels is our data is created by real people and it will always be created by real people because we are not selling a digital product we're selling good night's sleep and good night's sleep you can only do by yourself. not have your computer do it for you. So in our product, the people are physically there. So that makes it a lot easier. And we can learn a lot about this by just looking at the metadata and trying to understand the mass needs of our customers.

SPEAKER_01:
So when you're building a new hotel, do you start with, I guess this MVP had a chair in the room and then you realize that people are not actually using the chair. So did you then remove the chair from that hotel or did you just take that learning and apply it to the next hotel that you were building and just not order chairs from the beginning?

SPEAKER_02:
If you are building MVPs with bricks and mortar, you're not taking it away. And that's not possible. It's not like an IT where you just make a new website and it's yeah. So of course, this is only going into the planning of the next hotel and the next hotel. And it is important to find, you know, the optimum spacing for the optimum layout for the room like McDonald's did. a couple of years ago, they experiment or they still are doing it permanently to find the perfect layout of their stores and always renewing it. So every renewal cycle, of course, the chair goes, but it stays, of course, in the product till the life cycles of seven years is over. That is for sure. So we do have to think about our environment, too, and not just throw things away. So let's get to the end of the life of the product and then make it the right one. It's not harmful to have a chair in it. A lot of hotels have it, but in the next hotel, we're using the same resources for different sinks and different spaces. For example, we didn't change the hair dryers of the courts, but for every new hotel, when you are visiting us, you will find a long court in that that doesn't curl anything. So that was something you mentioned before that is completely true, that not only do they cheat, but also these little curl things seems to be a problem. We want the net promotion score to get higher for every guest experience, and I think we achieved that way. And a different finding, for example, is if you have the power management take away your card. I don't know if that's in the state too, but in Germany it is, because we're very sensitive there. All the electrical outlets are off. Our finding was that is a huge pain point for the customers. So we put it on the desk, all the outlets on the desk and next to the bed. So where you put your cell phone usually, even if you take the card out, your phone is still charging because once you're going, oh, I get quick go out for dinner and I only have 6%, but I need to make a different call later. So I'm picking, grabbing a bite, put it in. Yeah. And you're coming back and say, send or even lower than you were completely unsatisfied and are mad about the product. And this is a pain point we can take away very easy to say, OK, this outlet has permanent power. It doesn't pull any power environmental wise if you don't have a charging device in it. But if you have a charging device in it, it should have the power. So you could use a lot of smart technology to achieve that or you can say, OK, We just leave this electrical outlet always power on, and the customer is satisfied. It doesn't consume any more energy, and you have a perfect solution, which is low-tech. And low-tech is sometimes the best smart tech.

SPEAKER_01:
One thing we haven't talked about yet that I do want to dig into is CRM and how you maintain relationships with guests and also how you gather that sort of qualitative data. We've talked about the quantitative piece, like are people sitting in the chair and how much weight is on the chair, but what about how comfortable is the chair or are people satisfied with certain elements in the room? How do you gather that type of data?

SPEAKER_02:
That is actually, you know, heart data is easy to collect. I mean, weight is something very easy to collect. The quality of sleep is very difficult to collect and the quality of a pillow is even more difficult to measure because a pillow that is right for you might not be right for me. It's definitely not because as a male, we sleep best on a pillow that is 50 to 70 centimeters. And females sleep best depending on how they sleep out of their physical form on a more square. So 80 to 80 or 60 to 60 pillow and not too high and everything. So that is something where we are not going into it because we cannot make it yet. We'll take the scientific data out of other branches to see how that works. And there's a lot of medicine there. And so sleep is something that is where there's a lot of information. So we are not going into this kind of data yet because we cannot do it. And it would be a little bit too much invasion of privacy if we would go into something like that. So to be fair here, quality of sleep or this quality of things to measure, it's very difficult and we'll go on the common knowledge there. But you asked also about the quality of the data. And I think there is one very important part of it. And that comes, we are here on a technical podcast. So I might say, we usually have one unified identificator, for example, email address. And that's your, Adrian, your unique identifier for the database. We figured that is too weak. So our identifier is always out of multiple components building the data set. And so we have a lot better record of the data points you're leaving because we can match you a lot better to the data that are there. And even your transactional data, for example, the credit card payments and everything, We can match that to your profile and that's why we need a golden record or a data lake where all the data is stored in and not to have it into the CRM systems, if it's HubSpot or Salesforce or Dynamics Insight from Microsoft. it doesn't matter always the data is if you have it in this silo again it's not quality good enough to have all the data because you need to combine it with PMS data you need to combine it with all the other data you have in the hotel even with your Wi-Fi systems, you have to combine these data to ensure the quality of service you want to provide for your guests, for example, and the quality of service for video conferences is very important for the seamless thing. So we see when there's a lot of guest traffic, the quality of service of our Wi-Fi is more focusing on Teams, Zoom and all these devices and not about the streaming platforms. So actually, then Netflix goes down a little bit. Netflix is always Netflix, Disney and Co. I'm not just talking about, you know, these video on demand platforms and, you know, and the quality of service for the business platform is going up. And then you need to know what the mass of your customers are right now in your object.

SPEAKER_01:
I'm also curious how you think about guest reviews or any sort of surveys that you may send to guests. Are you also proactively asking them for some data points about their state?

SPEAKER_02:
Well, this is a little more difficult in Germany than in the States. In Germany, we have this privacy shield and privacy data, so you can only send surveys if you have an opt-in of the guest, a double opt-in or double opt-out if she doesn't want to be disturbed. And you have to be very careful with this data. So, of course, we're doing this, but this process is a lot more difficult than this metadata to analyze that. to have a quality-wise statistics-significant data, you need to build a huge setup. You're doing this once or twice a year to just, you know, see if your systems are measuring correct. But this is more, I would say, a calibration than the insights we're getting out because the data sets are too small.

SPEAKER_01:
Well, we are coming up on time. I have maybe one or two more questions we can get through. What would you say is on your wish list for new technology or maybe a new vendor that you've seen on the market that you find really interesting, something that you're considering implementing in your hotels but haven't done it yet?

SPEAKER_02:
Well, we are implementing it right now and therefore it is on my wish list. It's augmented reality. We're using it for our maintenance staff already. This only works on digital prints that we have in card store. There you have your tablet and you look, oh, the water is coming in our janitor, she is using her tablet to just find the right screw to open and close and that is a great thing. I would love to do this in classes and even get all the PMS data and everything in the classes augmented reality for our staff people to better care for the customer. And of course, what we're doing this now is our welcome desk where we already speak a lot of languages. We need to have the language barriers to do even work better with that. So it would be great to not only use Google Translate like a lot of people are using it once you have people where you cannot communicate with, but to simultaneously do that already with like we're doing it right now. If we were switching on, well, not this, but if you would have used Teams, we could live transcription and everything. So I think that would be great. If you hitchhike this guy to the galaxy, like this little worm you have in your ear, that would be the absolute greatest thing we could do in the hotel industry to even serve our customers better by speaking their language. We're doing it already with our staff because we figured out a lot of mistakes that are happening is because people don't understand that we are employing staff out of more than 40 nations in our company, and all the handbooks and everything were in German. And now we have the handbooks and everything in the cloud, of course, and people can check with it in their own language. And that reduces the mistakes a lot, because they can understand a lot easier. And for a computer, it doesn't matter if it's in English or in, let's say, Turkish or Bulgarian or French, we speak the language of our employees. Of course, you have to give every employee his or her own cell phone to use this technology. I know that is not common in the hotel industry, but that is, I think we, in the hospitality industry, we have to learn. So every staff of us has his own email address. She or he has his own cell phone. and can work with that. And the language of the cell phone is actually determined the language that the communication is taking place. And I wish we could bring that more to the guests, because that will make life a lot easier.

SPEAKER_01:
So this is one of my favorite questions to ask. What is one thing you believe about technology in the hotel world that your peers or competitors would disagree with?

SPEAKER_02:
I say it in German and then I say it in English. Daten und Fakten statt Bauchgefühl. It means data and facts instead of stomach feeling or gut feeling. I think it's English for it. And a lot of my colleagues maybe say yes, but then it stops. And I say, no, if the data tells us that's it, we're going that way.

SPEAKER_01:
Any final points or topics that you want to mention before we wrap up?

SPEAKER_02:
I think in the hospitality industry, we have a huge chance with this AI world we are going into now to get back our market shares because we can now completely work with our guests again and not need a lot of intermediaries in between. Because I think in the future, the guests and the hotel, those working as AI will talk to each other. Well, their AIs will talk to each other, but they will talk directly to each other. And so we will have not too much cost in this intermediary exchange and can spend a lot more money on the product and therefore make the guest experience even better in every level of their hotels.

SPEAKER_01:
Well, thank you so much, Martin. It was great meeting with you. Great chatting with you. Thank you for sharing all the details. Thank you.

SPEAKER_00:
That's all for today's episode. Thanks for listening to Hotel Tech Insider produced by Hoteltechreport.com. Our goal with this podcast is to show you how the best in the business are leveraging technology to grow their properties and outperform the concept by using innovative digital tools and strategies. I encourage all of our listeners to go try at least one of these strategies or tools that you learned from today's episode. Successful digital transformation is all about consistent small experiments over a long period of time. So don't wait until tomorrow to try something new. Do you know a hotelier who would be great to feature on this show? Or do you think that your story would bring a lot of value to our audience? Reach out to me directly on LinkedIn by searching for Jordan Hollander. For more episodes like this, follow Hotel Tech Insider on all major streaming platforms like Spotify and Apple Music.